On Fri, 2 Jun 2006 19:09:01 +0200
Joris De Ridder <joris at ster.kuleuven.be> wrote:
> Just to be sure, what exactly is affected when one uses the slower
> algorithms when neither BLAS or LAPACK is installed? For sure it
> will affect almost every function in numpy.linalg, as they use
> LAPACK_lite. And I guess that in numpy.core the dot() function
> uses the lite numpy/core/blasdot/_dotblas.c routine? Any other
> numpy functions that are affected?
Using a better default dgemm for matrix multiplication when an optimized
BLAS isn't available has been on my to-do list for a while. I think it
can be speed up by a large amount on a generic machine by using
blocking of the matrices.
Personally, I perceive no difference between my g77-compiled LAPACK,
and the gcc-compiled f2c'd routines in lapack_lite, if an optimized
BLAS is used. And lapack_lite has fewer bugs than the version of LAPACK
available off of netlib.org, as I used the latest patches I could
scrounge up (mostly from Debian).
--
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|David M. Cooke
http://arbutus.physics.mcmaster.ca/dmc/ |cookedm at physics.mcmaster.ca